In this thesis I present a framework for intelligent software agents to manage risk in electronic marketplaces using Option Derivatives. To compare the perfonnance of agents that trade Option Derivatives with agents not using them, I create a simulation of a financial marketplace in which software agents are vested with decision rules for buying and selling assets and Options. The motivation of my work is the need of risk management mechanisms for those Multi-Agent Systems where resources are allocated according to a market mechanism. Autonomous agents participating in such markets need to consider the risks to which they are exposed when trading in them, and to take actions to manage those risks. This thesis considers the hypothesis that software agents can benefit from trading Option Derivatives, using them as a tool to manage their exposure to uncertainty in the market. The main contributions of this thesis are: First, an abstract framework of an Option trading market is developed. This framework serves as a foundation for the implementation of computational Option trading mechanisms in systems using Market-Based resource allocation. The framework can be incorporated into existing Market-Based systems using the traded resources as the underlying assets for the Option market. Within the framework, four basic Option trading strategies are introduced, some of which reason about the risks exposed by their actions. These strategies are provided as a foundation for the development of more complex strategies that maximise the utility of the trading agents by the use of Options. The second contribution of this thesis is the analysis of the results from simulation experiments perfonned with the implementation of a software Multi-Agent System based on the developed Option trading framework. The system was developed in Java using the Repast simulation platfonn. The experiments were used to test the perfonnance of the developed trading strategies. This research shows that agents which traded Options by choosing actions aiming to minimize their risk perfonned significantly better than agents using other trading strategies, in the majority of the experiments. Agents using this risk-minimizing strategy also observed a lower correlation between the asset price and their returns, for the majority of the experimented scenarios. Agents which traded Options aiming to maximize their returns perfonned better than their peers in the scenarios where the asset price volatility was high. Finally, it was also observed that the perfonnance differential of the strategies increased as the uncertainty about the future price of the asset was increased.